A comparative analysis of metaheuristic algorithms in fuzzy modelling for phishing attack detection

• Main Authors: Nordin, Noor Syahirah, Ismail, Mohd. Arfian, Sutikno, Tole, Kasim, Shahreen, Hassan, Rohayanti, Zakaria, Zalmiyah, Mohamad, Mohd. Saberi
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2021
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/94806/1/ZalmiyahZakaria2021_AComparativeAnalysisofMetaheuristicAlgorithms.pdf; http://eprints.utm.my/id/eprint/94806/; http://dx.doi.org/10.11591/ijeecs.v23.i2.pp1146-1158

Phishing attack is a well-known cyber security attack that happens to many people around the world. The increasing and never-ending case of phishing attack has led to more automated approaches in detecting phishing attack. One of the methods is applying fuzzy system. Fuzzy system is a rule-based system that utilize fuzzy sets and fuzzy logic concept to solve problems. However, it is hard to achieve optimal solution when applied to complex problem where the process of identify the fuzzy parameter becomes more complicated. To cater this issue, an optimization method is needed to identify the parameter of fuzzy automatically. The optimization method derives from the metaheuristic algorithm. Therefore, the aim of this study is to make a comparative analysis between the metaheuristic algorithms in fuzzy modelling. The study was conducted to analyse which algorithm performed better when applied in two datasets: website phishing dataset (WPD) and phishing websites dataset (PWD). Then the results were obtained to show the performance of every metaheuristic algorithm in terms of convergence speed, and four metrics including accuracy, recall, precision, and f-measure.